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Record W2005231649 · doi:10.1021/ie8001974

Minimum Fluidization Velocity of a Three-Phase Conical Fluidized Bed in Comparison to a Cylindrical Fluidized Bed

2008· article· en· W2005231649 on OpenAlexaff
Dandan Zhou, Shuangshi Dong, Heli Wang, Hsiaotao T. Bi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2008
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConical surfaceFluidizationFluidized bedMechanicsPressure dropPhase (matter)Mixing (physics)Materials scienceThermodynamicsThree-phaseChemistryPhysicsComposite material

Abstract

fetched live from OpenAlex

Hydrodynamic characteristics of a gas−liquid−solid conical fluidized bed were studied and compared with both liquid−solid conical beds and three-phase cylindrical fluidized beds. The effect of bubbles on particle mixing, pressure drop, and minimum fluidization velocity were discussed. Minimum fluidization velocities predicted by modified Ergun equation which accounts for the variation of the cross-sectional area with the bed height were found to be in good agreement with the liquid−solid conical fluidized bed data. The models of Song et al. [ Can. J. Chem. Eng. 1989, 67, 265] and Zhang et al. [ Power Tech. 1998, 100, 113; PhD. Thesis, 1996 ], derived originally for three-phase cylindrical fluidized beds, respectively, were modified for the prediction of U mf in a three-phase conical fluidized bed by accounting for the geometrical variation of the conical bed. It is found that the modified Song et al. model gave a better agreement than the modified Zhang et al. model in comparison with the current experimental data. However, the prediction of the modified Zhang et al. model is much improved when the parameter α, fractional gas holdup, was estimated using the equation from the Song et al. model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.117
GPT teacher head0.345
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2008
Admission routes1
Has abstractyes

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